Remove Data Quality Remove Data Transformation Remove Marketing
article thumbnail

The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data.

article thumbnail

IKEA’s Data Transformation: Lessons from a Global Giant

Timo Elliott

In a recent presentation at the SAPSA Impuls event in Stockholm , George Sandu, IKEA’s Master Data Leader, shared the company’s data transformation story, offering valuable lessons for organizations navigating similar challenges. “Every flow in our supply chain represents a data flow,” Sandu explained.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

How ANZ Institutional Division built a federated data platform to enable their domain teams to build data products to support business outcomes

AWS Big Data

Domain ownership recognizes that the teams generating the data have the deepest understanding of it and are therefore best suited to manage, govern, and share it effectively. This principle makes sure data accountability remains close to the source, fostering higher data quality and relevance.

Metadata 105
article thumbnail

Ensuring Data Transformation Quality with dbt Core

Wayne Yaddow

How dbt Core aids data teams test, validate, and monitor complex data transformations and conversions Photo by NASA on Unsplash Introduction dbt Core, an open-source framework for developing, testing, and documenting SQL-based data transformations, has become a must-have tool for modern data teams as the complexity of data pipelines grows.

article thumbnail

What is Data Lineage? Top 5 Benefits of Data Lineage

erwin

Data is crucial to every organization’s survival. For that reason, businesses must think about the flow of data across multiple systems that fuel organizational decision-making. For example, the marketing department uses demographics and customer behavior to forecast sales. Data Quality.

article thumbnail

How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

cycle_end";') con.close() With this, as the data lands in the curated data lake (Amazon S3 in parquet format) in the producer account, the data science and AI teams gain instant access to the source data eliminating traditional delays in the data availability.

IoT 111
article thumbnail

Is your data supply chain a liability?

CIO Business Intelligence

Yet as companies fight for skilled analyst roles to utilize data to make better decisions , they often fall short in improving the data supply chain and resulting data quality. Without a solid data supply-chain management practices in place, data quality often suffers. First mile/last mile impacts.